White matter hyperintensities are associated with subthreshold amyloid accumulation
Bibliographic record
Abstract
The association between white matter hyperintensities (WMH) and amyloid accumulation over time in cognitively normal, amyloid-negative elderly people remains largely unexplored. In order to study whether baseline WMH were associated with longitudinal subthreshold amyloid accumulation, 159 cognitively normal participants from the Alzheimer's Disease Neuroimaging Initiative who were amyloid-negative at baseline were examined. All the participants underwent a T1 and a Fluid-Attenuated Inversion Recovery MRI scan at baseline. Amyloid PET imaging was performed at baseline and follow-up visits in 2-year intervals for up to 8 years. Partial volume correction was applied for quantifying cortical Standardised Uptake Value Ratios (SUVR). The associations between global and regional WMH burden and amyloid accumulation were assessed using linear mixed models adjusted by demographic characteristics and baseline SUVR. Partial volume correction increased the measured annual rate of change (+2.4%) compared to that obtained from non-corrected data (+0.5%). There were no significant correlations between baseline WMHs and baseline subthreshold cortical amyloid uptake. In a longitudinal analysis, increased baseline cortical SUVR and increased baseline burden of global (p = 0.006), frontal (p = 0.006), and parietal WMH (p = 0.003) were associated with faster amyloid accumulation. WMH-related amyloid accumulation occurred in parietal, frontal, and, to a lesser extent, cingulate cortices. These results remained unchanged after a sensitivity analysis excluding participants with the highest cortical SUVRs. This is the first study to identify a specific spatial distribution of WMH which is associated with future amyloid accumulation in cognitively normal elderly subjects without PET-detectable amyloid pathology. These findings may have important implications in prevention trials for the early identification of amyloid accumulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".